The increasing availability of smart phones equipped with GPS and powerful processors, such as e.g. Android phones, has provided for a large and increasing market for LBS (Location-Based Services). This is a type of services that create end-user value based on information that is closely tied to geographical location data. Many LBS based applications strongly rely on the availability of digital maps.
One factor that has contributed to the great success of LBS is the public availability to maps and APIs (Application Programming Interfaces) which are configured to provide access to, and to enable users to build applications that utilize these maps. These options have made it possible for any developer with at least some basic programming skills to create LBS applications that can deliver great value to its users.
Up until recently almost all available LBS have been targeted for outdoor use. Recent development in positioning technology and map creation tools have however started to enable LBS focused also on indoor use. In addition, an increasing number of maps describing indoor locations have also recently been made available to the public.
There are various strategies to be used for creating indoor maps. One way, which may be referred to as surveying, rely on personnel which is instructed to survey buildings, typically assisted with survey tools, such as e.g. laser or radar equipment, and to draw up maps based on those surveys.
Alternatively, map providers may apply sourcing of building schematics, which can be achieved by setting up deals with property owners, such that property can be mapped to provide descriptive schematics and drawings which make up maps of the respective properties.
Crowd sourcing is yet another alternative way of providing maps where map providers encourage the public to use their available tools to draw up maps of different locations that might be of public interest. These maps are then stored in a proprietary format specified by the map provider and made available to map developers, such that the map providers can use this data to create various types of LBS applications that will be applicable in mapped locations.
Available outdoor LBS normally rely on the widespread availability of digital maps. These digital maps are typically produced and provided by large companies that use a combination of manual surveying and purchasing of government provided information to create and provide detailed geographical maps. When it comes to indoor maps, however, there are at least two big challenges when it comes to management and distribution of such maps.
One problem with maps displaying indoor locations is that no central repository of information about the locations exists. Building schematics and layouts of different properties, or even the same property, are often owned by different companies, such as e.g. constructing companies, building owners or companies responsible for the maintenance of the buildings. Such information is in most cases not made available to the public and consequently there is no central storage where this information can be accessed. The companies that have made an effort in assembling this type of information so as to be able to create maps of indoor locations are normally using their own proprietary map technologies, thereby leaving a developer who wants to build LBS applications based on the same information with the only option of relying on the map technology presently used and provided by the respective company, if that technology is at all made available for external use.
Another problem with the described type of map providing systems, such as e.g. systems based on crowd sourcing, where a lot of different persons contribute in creating maps, is that it is difficult to control which map that should be used by which application. Many users may have provided a range of different maps for the same building or for the same section of a building. In each situation there is generally one available map that is more suitable than the rest, depending on the circumstances, e.g. due to having the best quality for the required task, while in other case other maps may be more useful and illustrative. A map optimized for real-estate maintenance or security personnel will e.g. most certainly in most cases not be the most suitable map for mall customers wanting to know where to find a specific product.
A typical well known system which is configured to manage and make available maps to mobile users is schematically illustrated in FIG. 1, where the system 10 comprises a map server 11 which is connected to a plurality of map databases 12,13,14, containing a plurality of maps, such that all maps available from the map databases 12,13,14 a can be exposed, typically via an API, and made accessible to user devices 15 from the map server 11. An en user may access and use stored maps by connecting to the API of map server 11 from a map application running on the user device 15.
One problem when implementing a solution as suggested in FIG. 1 is to be able to configure a map server that can provide maps which are suitable for a vide variety of different types of map related applications and services. When an application requests map data from a map server, the map server will typically provide information about the geographical location for which the end-user requires a map. If there are multiple maps available in one location it is up to the end-user to use his judgment to decide which map is the most suitable from one situation to the other. However, it is often very difficult to determine which map that is the most suitable one, and one can often not judge whether the selected map was an appropriate one before having used the selected map for a while.
It is also very difficult to design a map server that is suitable for handling all types of map related applications. While one type of applications may be adapted to select maps which provide the best information about certain products in different retail stores, another type of applications may be adapted to select maps based on previous usage of the maps, e.g. on the basis of users comments and/or ratings, while yet another type of applications may instead be adapted to provide maps specifically provided by one or more specific supplier. All these various demands raise a need for a map server which is configured such that it provide for a more flexible and efficient map selection approach.